Virtual Field Geologic Trip System (VFGTS) constructed by the technique of visualization can efficiently present geologic field information and widely used in the field of geologic education. This paper introduces the...Virtual Field Geologic Trip System (VFGTS) constructed by the technique of visualization can efficiently present geologic field information and widely used in the field of geologic education. This paper introduces the developing thinking of VFGTS and discusses the main implement processes. Building VFGTS mainly includes systemically gathering of field geological data, the building of virtual geological world, and displaying of virtual geologic world and human-computer interaction.展开更多
Stainless steels are used in a wide range of complex environments due to their excellent corrosion resistance.Multiphase stainless steels can offer an excellent combination of strength,toughness and corrosion resistan...Stainless steels are used in a wide range of complex environments due to their excellent corrosion resistance.Multiphase stainless steels can offer an excellent combination of strength,toughness and corrosion resistance due to the coexistence of different microstructures.The microstructure and mechanical properties of a novel cast multiphase stainless steel,composed of martensite,ferrite,and austenite,were investigated following appropriate heat treatment processes:solution treatment at 1,050℃ for 0.5 h followed by water quenching to room temperature,and aging treatment at 500℃ for 4 h followed by water quenching to room temperature.Results show reversed austenite is formed by diffusion of Ni element during aging process,and the enrichment of Ni atoms directly determines the mechanical stability of austenite.The austenite with a lower Ni content undergoes a martensitic transformation during plastic deformation.The tensile strength of the specimen exceeds 1,100 MPa and the elongation exceeds 24%after solid solution,and further increases to 1,247 MPa and 25%after aging treatment.This enhancement is due to the TRIP effect of austenite and the precipitation of the nanoscale G-phase pinning dislocations in ferrite and martensite.展开更多
Foreign tourists'trips to China recently reached a new height,both online and offline.Travel agents around the world also made trips to China,generating more thoughts for the development of new routes and the desi...Foreign tourists'trips to China recently reached a new height,both online and offline.Travel agents around the world also made trips to China,generating more thoughts for the development of new routes and the design of innovative tourist products,and contributing to the development of China's inbound tourism.展开更多
Determining trip purpose is an important link to explore travel rules. In this paper,we takea utomobile users in urban areas as the research object,combine unsupervised learning and supervised learningm ethods to anal...Determining trip purpose is an important link to explore travel rules. In this paper,we takea utomobile users in urban areas as the research object,combine unsupervised learning and supervised learningm ethods to analyze their travel characteristics,and focus on the classification and prediction of automobileu sers’trip purposes. However,previous studies on trip purposes mainly focused on questionnaires and GPSd ata,which cannot well reflect the characteristics of automobile travel. In order to avoid the multi-dayb ehavior variability and unobservable heterogeneity of individual characteristics ignored in traditional traffic questionnaires,traffic monitoring data from the Northern District of Qingdao are used,and the K-meansc lustering method is applied to estimate the trip purposes of automobile users. Then,Adaptive Boosting(AdaBoost)and Random Forest(RF)methods are used to classify and predict trip purposes. Finally,ther esult shows:(1)the purpose of automobile users can be mainly divided into four clusters,which includeC ommuting trips,Flexible life demand travel in daytime,Evening entertainment and leisure shopping,andT axi-based trips for the first three types of purposes,respectively;(2)the Random Forest method performss ignificantly better than AdaBoost in trip purpose prediction for higher accuracy;(3)the average predictiona ccuracy of Random Forest under hyper-parameters optimization reaches96.25%,which proves the feasibilitya nd rationality of the above clustering results.展开更多
文摘Virtual Field Geologic Trip System (VFGTS) constructed by the technique of visualization can efficiently present geologic field information and widely used in the field of geologic education. This paper introduces the developing thinking of VFGTS and discusses the main implement processes. Building VFGTS mainly includes systemically gathering of field geological data, the building of virtual geological world, and displaying of virtual geologic world and human-computer interaction.
基金supported by the Inner Mongolia Autonomous Region Science and Technology Major Special Project(Grant No.2021SZD0082).
文摘Stainless steels are used in a wide range of complex environments due to their excellent corrosion resistance.Multiphase stainless steels can offer an excellent combination of strength,toughness and corrosion resistance due to the coexistence of different microstructures.The microstructure and mechanical properties of a novel cast multiphase stainless steel,composed of martensite,ferrite,and austenite,were investigated following appropriate heat treatment processes:solution treatment at 1,050℃ for 0.5 h followed by water quenching to room temperature,and aging treatment at 500℃ for 4 h followed by water quenching to room temperature.Results show reversed austenite is formed by diffusion of Ni element during aging process,and the enrichment of Ni atoms directly determines the mechanical stability of austenite.The austenite with a lower Ni content undergoes a martensitic transformation during plastic deformation.The tensile strength of the specimen exceeds 1,100 MPa and the elongation exceeds 24%after solid solution,and further increases to 1,247 MPa and 25%after aging treatment.This enhancement is due to the TRIP effect of austenite and the precipitation of the nanoscale G-phase pinning dislocations in ferrite and martensite.
文摘Foreign tourists'trips to China recently reached a new height,both online and offline.Travel agents around the world also made trips to China,generating more thoughts for the development of new routes and the design of innovative tourist products,and contributing to the development of China's inbound tourism.
基金Sponsored by the National Key R&D Program of China(Grant No.2020YFB1600500)the National Natural Science Foundation of China(GrantN o.52272319)。
文摘Determining trip purpose is an important link to explore travel rules. In this paper,we takea utomobile users in urban areas as the research object,combine unsupervised learning and supervised learningm ethods to analyze their travel characteristics,and focus on the classification and prediction of automobileu sers’trip purposes. However,previous studies on trip purposes mainly focused on questionnaires and GPSd ata,which cannot well reflect the characteristics of automobile travel. In order to avoid the multi-dayb ehavior variability and unobservable heterogeneity of individual characteristics ignored in traditional traffic questionnaires,traffic monitoring data from the Northern District of Qingdao are used,and the K-meansc lustering method is applied to estimate the trip purposes of automobile users. Then,Adaptive Boosting(AdaBoost)and Random Forest(RF)methods are used to classify and predict trip purposes. Finally,ther esult shows:(1)the purpose of automobile users can be mainly divided into four clusters,which includeC ommuting trips,Flexible life demand travel in daytime,Evening entertainment and leisure shopping,andT axi-based trips for the first three types of purposes,respectively;(2)the Random Forest method performss ignificantly better than AdaBoost in trip purpose prediction for higher accuracy;(3)the average predictiona ccuracy of Random Forest under hyper-parameters optimization reaches96.25%,which proves the feasibilitya nd rationality of the above clustering results.